A factored display emits full-parallax dense-view light fields for a glasses-free 3D experience without sacrificing the spatial resolution of a liquid-crystal display (LCD). For static light fields, it achieves high-quality reconstruction by applying frame-based low-rank factorization to time-multiplexed sub-frame contents of stacked LCDs. However, for light field videos such frame-based factorization could introduce reconstruction artifacts and visual flickers and further cause human discomfort. The artifacts mainly come from incomplete constraints for the emitted light fields that are actually perceived in continuous time, instead of discrete frames. In particular, the perceived light fields are related to the persistence-of-vision (POV) effect of human eyes and the refresh rates of LCD displays, which is not well explored in previous work. In this work, we introduce a light-field video factorization framework-temporal fusion (TF)-to resolve these issues. To begin with, we explicitly formulate the continuous-time POV effect into a global factorization objective functional to eliminate visual flickers and enhance image quality. We further show that this optimization problem can be solved by sequence-level iterative updates on LCD sub-frames. Then, to tackle the enormous requirement of memory access for the sequence-level processing flow, we devise an efficient cuboid-wise factorization algorithm which enables practical GPU implementation. We also devise another lightweight causal framework, TF-C, for supporting low-latency applications. Finally, extensive experiments are performed to verify the effectiveness. Compared to the plain frame-based factorization, TF/TF-C can improve temporal consistency by reducing flicker values by 85%/91% and enhance reconstruction quality by increasing PSNR values by 5.0dB/3.7dB. In addition, we present a prototype dual-layer factored display, which was built with two 240-Hz high-refresh-rate LCDs, to demonstrate the visual quality for real-life applications.

This article introduces a VLSI design for light-field factorization, aimed at enhancing immersive 3-D visual experiences for computational light-field factored displays. The main design challenges are intensive memory-access demands and high computational complexity. Accordingly, we first propose half-block-based factorization (HBBF) and sparse ray sampling (SRS) to reduce DRAM bandwidth by 99% and SRAM size by 74%. Then, we devise integer hybrid quantization (INTH) to cut down computational logic by 41%, leading to improvements in die area and power efficiency. Finally, we fabricated a processor chip that incorporates 75.1 kB of SRAM and 5.9M logic gates using 40-nm CMOS technology. It can operate with three different performance modes: high quality (56.9 MPixel/s at 971 mW), balanced (62.5 MPixel/s at 442 mW), and low power (61.7 MPixel/s at 283 mW). Across these modes, its normalized energy ranges between 4.4 and 16.2 nJ/pixel. This implementation surpasses existing GPU platforms and offers an$85\times $increase in processing speed and a$311\times $reduction in power consumption. We also showcase a real-time computational 3-D display system with this chip, demonstrating its practical efficacy in computational 3-D display technology.